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rdf:type |
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lifeskim:mentions |
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pubmed:dateCreated |
2009-2-19
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pubmed:abstractText |
Proteomic data is a potentially rich, but arguably unexploited, data source for genome annotation. Peptide identifications from tandem mass spectrometry provide prima facie evidence for gene predictions and can discriminate over a set of candidate gene models. Here we apply this to the recently sequenced Aspergillus niger fungal genome from the Joint Genome Institutes (JGI) and another predicted protein set from another A.niger sequence. Tandem mass spectra (MS/MS) were acquired from 1d gel electrophoresis bands and searched against all available gene models using Average Peptide Scoring (APS) and reverse database searching to produce confident identifications at an acceptable false discovery rate (FDR).
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pubmed:grant |
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pubmed:commentsCorrections |
http://linkedlifedata.com/resource/pubmed/commentcorrection/19193216-10612281,
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http://linkedlifedata.com/resource/pubmed/commentcorrection/19193216-9915494
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pubmed:language |
eng
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pubmed:journal |
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pubmed:citationSubset |
IM
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pubmed:status |
MEDLINE
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pubmed:issn |
1471-2164
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pubmed:author |
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pubmed:issnType |
Electronic
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pubmed:volume |
10
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
61
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pubmed:dateRevised |
2009-11-18
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pubmed:meshHeading |
pubmed-meshheading:19193216-Amino Acid Sequence,
pubmed-meshheading:19193216-Aspergillus niger,
pubmed-meshheading:19193216-Cluster Analysis,
pubmed-meshheading:19193216-Databases, Protein,
pubmed-meshheading:19193216-Genome, Fungal,
pubmed-meshheading:19193216-Models, Genetic,
pubmed-meshheading:19193216-Molecular Sequence Data,
pubmed-meshheading:19193216-Proteomics,
pubmed-meshheading:19193216-Sequence Alignment,
pubmed-meshheading:19193216-Tandem Mass Spectrometry
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pubmed:year |
2009
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pubmed:articleTitle |
Exploiting proteomic data for genome annotation and gene model validation in Aspergillus niger.
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pubmed:affiliation |
Dept Veterinary Preclinical Sciences, University of Liverpool, Liverpool, UK. james.wright@manchester.ac.uk
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pubmed:publicationType |
Journal Article,
Research Support, Non-U.S. Gov't
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